Applications for 2024 post-graduate studies are
closed. Closing date for post-graduate studies in 2025 is 31 October 2024. Please visit
www.sun.ac.za for details on the application process. All the postgraduate programmes are offered on campus - hence not online nor remotely.
Please note that all our postgraduate programmes are selection programmes. Apart from adhering to the minimum requirements per programme (Honours and/or Masters), selection is further done on excellent academic merit and only a limited number of students may be admitted to any such programme. Adhering to only the minimum requirements does not guarantee automatic admission.
Here you can find information on the following postgraduate programmes in Mathematical Statistics:
A short description and summary of the department's postgraduate modules can be found by clicking on a specific module or go to the bottom of this page. For more information, contact Prof Lubbe at
slubbe@sun.ac.za.
The R-module starts two weeks before official lectures start in 2024 (31 January). Compulsory module to all honours students in the Department.
Special registration for honours and masters modules
Students who wish to register for any of these post graduate modules as part of a degree offered outside the Department of Statistics and Actuarial Science, need to formally apply to the department for the module(s) by:
·
Send personal / contact details;
·
the module(s) you wish to apply for, as well as the degree you will be registered for, to
hrandall@sun.ac.za &
slubbe@sun.ac.za;
·
Attach a complete study record to your e-mail;
·
Make sure of the prerequisites of the modules you wish to apply for at
http://www.sun.ac.za/english/faculty/economy/statistics/programmes/mathematical-statistics/math-stats-postgraduate or
http://www.sun.ac.za/english/faculty/economy/statistics/programmes/statistics/stats-postgraduate, specifically regarding the R block module which takes place roughly two weeks before normal lecturing starts.
·
Closing date for applications is 30 January each year (and 20 January for 13074-723 Introduction to R).
22853 – 778 (120)BComHons in Economics and Mathematical Statistics
See the Faculty Calendar here for a detail description of this program.
22853 – 778 (120)BComHons in Mathematical Statistics (Focus on Data Science)
See the Faculty Calendar here for a detail description of this program.
This program is presented jointly by the Department of Statistics and Actuarial Science and the Department of Computer Science. Consequently students have to be admitted to postgraduate study by both these departments. A bachelor's degree with an average mark of at least 65% in Mathematical Statistics 3 is required, together with a satisfactory mark of at least 65% in Computer Science up to at least second year level.
Compulsory modules presented in this program:
Elective modules (these have to be selected taking into account the modules from Computer Science):
* This module follows the A module.MSA A need to be completed before the MSA B module can be taken.
22853 – 778 (120)BComHons in Mathematical Statistics
See the Faculty Calendar here for a detail description of this program. Modules presented in this program:
NA - This module is not presented in 2024.
* This module follows the A module.MSA A need to be completed before the MSA B module can be taken.
Module Content- Honours
Bayesian Statistics (10394-711)
Objectives and
content:The aim of the module is to introduce the students to the basic principles of Bayesian Statistics and its applications. Students will be able to identify the application areas of Bayesian Statistics. The numerical methods often used in Bayesian Analysis will also be demonstrated. Topics:Decision theory in general; risk and Bayesian risk in Bayesian decisions; use of non-negative loss functions; construction of Bayesian decision function; determining posteriors; sufficient statistics; class of natural conjugate priors; marginal posteriors; class of non-informative priors; estimation under squared and absolute error loss; Bayesian inference of parameters; Bayesian hypothesis testing; various simulation algorithms for posteriors on open source software; numerical techniques like Gibbs sampling and the Metropolis-Hastings algorithm, as well as MCMC methods to simulate posteriors.
Biostatistics (10408-712)
Objectives and content:Biostatistics may be regarded as the study of the application of statistics to medicine. It covers medical terminology, the design of clinical trials, the collection and numerical analysis of data, the interpretation of the analyses and the drawing of conclusions. Particular emphasis is given to skills relevant to medical literature (the writing, as well as the understanding of writing by others) and statistical techniques and software that are widely used when doing
